Prostate cancer is the leading cancer among men in the United States. Multiple studies have consistently demonstrated a genetic component of the disease. Sequence variants in many major and modifier genes have been hypothesized to increase disease susceptibility. If these sequence variants do predispose to prostate cancer, they will be over-represented among men with prostate cancer, which can be detected using a case-control association study design. However, the search for these variants using association studies is a daunting task because of the formidable cost associated with a large number of potential candidate genes and a large number of mutations within these candidate genes. An alternative approach is to estimate allele frequencies from pooled DNA of hundreds of subjects, therefore significantly decreasing the number of genotyping assays. While the validity and statistical power of this approach have been demonstrated, the application of this method in large-scale population studies remains scarce, suggesting additional research is needed to refine the method and to provide guidelines for applying this method in a 'real world' association study. A major goal of this applicant is to test the utility of this method in a large-scale association study and to generate first hand experience from the perspective of an application, rather than methods development, of this technology. We will address several important questions, including the percentage of SNPs that are suitable for pooled analysis, the possibility and extent of multiplexing SNPs in pooled analysis, the accuracy in estimating allele frequencies in various scenarios, and the cost savings using pooled DNA analysis versus individual SNP genotyping. We will apply our pooled analysis to test for associations between prostate cancer risk and a large number of SNPs in 10 Toll-like Receptor (TLR) genes among 2,411 prostate cancer cases and 1,899 controls from Sweden. The results from this study will provide a basis, for our group and for other research groups, to practically and systematically screen a large number of SNPs for association with prostate cancer risk.